After 17 years, we finally “cracked” a $100M churn problem at PayPal. Zero fancy tech. Just a spreadsheet, some simple SQL, and a physicist named Ben. 👇🏼 (View Tweet)
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We narrowed it down by applying exclusions, crossing off things that look like churn, but aren’t. What can we rule out first? Account closures. (View Tweet)
Almost nobody ever closes a PayPal account, because there’s no monthly fee. They just stop transacting. So we needed to look at accounts who “go dark.” (View Tweet)
(By the time customers cancel it’s too late! They may have given up on your product months or years earlier - look for behavioral churn.) The next thing we excluded were “one-and-dones.” (View Tweet)
Many businesses sign up for PayPal accounts, get paid a bit, and then “go dark.” We found that most of them are small / occasional users who don’t really need the product every day. That’s
Not much revenue and
Not addressable anyways.
Off the list. (View Tweet)
What about new signups with legit businesses who have a bad first experience? That’s a serious problem! But it’s not churn. It’s an onboarding & activation problem. (That may sound like splitting hairs, but it’s an important distinction…) (View Tweet)
(If you go on a first date with somebody, and they ghost you, that is not a “divorce” it’s an “activation” problem.) (View Tweet)
We also had “false positives” who stop transacting for a while, and then predictably re-start. (e.g. halloween costume stores, monthly billers, Burning Man, etc.)
Also, a bit of churn is “non-regretted”: people we kicked off the platform for bad behavior. Rule them out. (View Tweet)
Note: The Halloween stores would not fit PayPal’s primary use case. Seasonal stores are a secondary use case. It was smart of them to exclude them from the analysis and focus on the primary.
So now we’re down to tenured, well-behaved, non-seasonal merchants who “go dark.” Unfortunately, that’s still hundreds of thousands of accounts. We need to make another cut. (View Tweet)
PayPal’s B2B revenue is quite concentrated: ~90% of revenue comes from ~10% of their merchants. So we focused on revenue churn rather than account churn. That narrowed the problem considerably! - maybe a couple hundred merchants per year. (View Tweet)
PayPal long ago fixed the major customer experience “killers.” Now it’s all “death by a thousand paper cuts” scenarios. How do you find a thousand paper cuts? You get a summer intern, that’s how! 😀 (View Tweet)
Our diligent intern spent months reconstructing each history - logging into every system: Risk, compliance, customer service, etc. to see where we screwed up. (Getting access to systems was half the work!) (View Tweet)
Next, he bucketed them into about 20 “killer” scenarios… and we had our “fancy predictive model” and ready to take action! (View Tweet)
(By ‘fancy predictive model’ I mean Ben ran queries each week to flag merchants hitting any of 20 killer scenarios.) He’d send the results to customer service, who would call the customers and fix the problems. (View Tweet)
Note: Low tech solution - high impact results
The merchants we helped were delighted. (And the shareholders should be too!) So, if you have a churn problem, here’s how to focus your thinking: (View Tweet)
Focus on behavioral churn, cancellation is too late
Separate activation from retention - use different fixes
Focus only on addressable & regretted
Account churn vs. revenue churn - is your revenue concentrated?
Then, dig into the details! (Intern optional). (View Tweet)
Since fixing at scale was too hard, we narrowed down the problem to solve at a sub-scale level.
Helpful? I send a 2-minute/week email to help founders learn enough about startup growth to be dangerous 😈. You can read them all & subscribe here. https://t.co/mgs2GtnnKZ (View Tweet)
